Mathematical modeling of terrorism dynamics: Qualitative analysis and theoretical perspective

被引:0
作者
Kumar, Abhishek [1 ]
Goel, Kanica [2 ]
Nilam [3 ]
机构
[1] Univ Delhi, Deshbandhu Coll, Dept Math, Delhi 110019, India
[2] Univ Delhi, Shyama Prasad Mukherji Coll Women, Dept Math, Delhi, India
[3] Delhi Technol Univ, Dept Appl Math, Delhi, India
关键词
counter-terrorism approach; influence time; mathematical model; simulation; stability; terrorism;
D O I
10.1002/mma.9769
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Terrorism has become a daily occurrence in our world, and governments and security forces around the world are highly concerned about stopping or minimizing terrorist activities. This study proposes a new approach to counter-terrorism through compartmental mathematical modeling on underlying principles of terrorism, such as recruiting new terrorists, military interventions, limitations in military interventions, desertion from the group, and influence time. We introduce the influence time in the present terrorism model to include the time it takes for a person to become a member of a terrorist group when effectively attracted. A system of delay differential equations is proposed to model terrorism dynamics. The model results are analyzed and investigated through qualitative analysis for two obtained equilibria, namely, a terrorism-free equilibrium and terrorism-persistent equilibrium. Finally, some numerical results support our analytical findings and demonstrate the effectiveness of the proposed counter-terrorism mathematical modeling approach. This study enhances the theoretical understanding of policymakers on terrorism mitigation and offers valuable insights into developing effective counter-terrorism strategies.
引用
收藏
页码:32 / 51
页数:20
相关论文
共 17 条
[1]  
Abiodun OI, 2018, INT J COMPUT SCI NET, V18, P117
[2]   Dynamical models of tuberculosis and their applications [J].
Castillo-Chavez, C ;
Song, BJ .
MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2004, 1 (02) :361-404
[3]   Optimal control of terrorism and global reputation: A case study with novel threshold behavior [J].
Caulkins, J. P. ;
Feichtinger, G. ;
Grass, D. ;
Tragler, G. .
OPERATIONS RESEARCH LETTERS, 2009, 37 (06) :387-391
[4]   MODELING AND ANALYSIS OF AN SEIR MODEL WITH DIFFERENT TYPES OF NONLINEAR TREATMENT RATES [J].
Dubey, B. ;
Patra, Atasi ;
Srivastava, P. K. ;
Dubey, Uma S. .
JOURNAL OF BIOLOGICAL SYSTEMS, 2013, 21 (03)
[5]   A deterministic time-delayed SVIRS epidemic model with incidences and saturated treatment [J].
Goel, Kanica ;
Kumar, Abhishek ;
Nilam .
JOURNAL OF ENGINEERING MATHEMATICS, 2020, 121 (01) :19-38
[6]   Understanding Terrorist Organizations with a Dynamic Model [J].
Gutfraind, Alexander .
STUDIES IN CONFLICT & TERRORISM, 2009, 32 (01) :45-59
[7]  
Hale J.K., 1993, Introduction to Functional Differential Equations
[8]  
Kuang Y., 1993, Delay Differential Equations with Applications in Population Dynamics
[9]   A study on the stability behavior of an epidemic model with ratio-dependent incidence and saturated treatment [J].
Kumar, Abhishek ;
Kumar, Manoj ;
Nilam .
THEORY IN BIOSCIENCES, 2020, 139 (02) :225-234
[10]   ANALYSIS ON AN EPIDEMIC MODEL WITH A RATIO-DEPENDENT NONLINEAR INCIDENCE RATE [J].
Li, Bo ;
Yuan, Sanling ;
Zhang, Weiguo .
INTERNATIONAL JOURNAL OF BIOMATHEMATICS, 2011, 4 (02) :227-239